基于波束域LC-GSC的降秩波束形成算法

A Reduced Rank Beamforming Algorithm Based on Beam Domain LC-GSC

针对传统GSC算法在处理大型阵列天线时,所需运算量大、工程上难以应用等问题,提出一种基于波束域LC-GSC的降秩波束形成算法。与传统GSC算法相比,它能够在期望信号和特定干扰方向上形成约束响应,利用构造的转换矩阵将信号变换到波束域,并能够降低计算量,加快自适应收敛速度。根据信号特征值大于噪声特征值,可以得到波束域协方差矩阵逆的高次幂基本等价于信号子空间,信号子空间的求取也方便构造阻塞矩阵。降秩矩阵可以利用GSC下支路的快拍数构造,进一步降低运算量。最终根据算法得到自适应权矢量,为了使系统有更好的信噪比稳健性,可以将权矢量向信号子空间投影。通过对GSC算法进行分析并改进,给出算法在FPGA上的实现方案。实验仿真表明,该算法能够在期望信号方向准确形成主瓣,干扰方向准确形成零陷且副瓣电平降低5~10dB。基于波束域LC-GSC的降秩波束形成算法有很好的波束形成性能,算法稳健性较好。

When the traditional GSC algorithm is used to process large array antennas,it requires a large amount of computation and is difficult to apply in engineering.In this paper,a beam-domain LC-GSC-based reduced rank beamforming algorithm is proposed.Compared with the traditional GSC algorithm,it can form a constrained response in the desired signal and the specific interference direction,transform the connected signal into the converted matrix,and reduce the amount of calculation.The speed of the adaptive convergence can be accelerated.Then,according to the signal eigenvalue greater than the noise eigenvalue,the inverse power of the beam domain covariance matrix can be obtained,which is substantially equivalent to the signal subspace.The calculation of the signal subspace also facilitates the construction of the blocking matrix.The rank reduction matrix can be constructed by using the snapshot number of the branch under the GSC,which further reduces the amount of calculation.Finally,the adaptive weight vector is obtained according to the algorithm.In order to make the system have better signal-to-noise ratio robustness,the weight vector can be projected to the signal subspace.Through the analysis and improvement of the GSC algorithm,the implementation scheme of the algorithm on the FPGA is given.Experimental simulations show that the proposed algorithm can accurately form the main lobe in the desired signal direction,the interference direction accurately forms a null trap and the sidelobe level also has a 5~10 dB reduction.The beam-slope LC-GSC-based reduced rank beamforming algorithm has good beamforming performance and good algorithm robustness.